$ cat jobs/manager-data-science-dynamic-promo-quick-commerce-deliveryhero-3099e79c562e.json
Manager, Data Science, Dynamic Promo - Quick Commerce
As the world’s pioneering local delivery platform, our mission is to deliver an amazing experience, fast, easy, and to your door. We operate in around 65 countries worldwide, powered by tech, designed by people. As one of Europe’s largest tech platforms, headquartered in Berlin, Germany, Delivery Hero has been listed on the Frankfurt Stock Exchange since 2017 and is part of the MDAX stock market index. We push hard, learn quickly and stay human along the way. It’s this wonderful mix of high performance and real community that makes Delivery Hero a place where ambition and belonging grow side by side. If you’re curious, collaborative and ready to dive deep into meaningful work, you’ll fit right in. We are on the lookout for a Manager, Data Science, Dynamic Promo, to join Quick Commerce on our journey to always deliver amazing experiences. Be part of redefining how customers experience quick commerce. You’ll help build technology that scales our non-food offerings, reaching new market segments and driving revenue growth. By innovating within our Quick Commerce Team, you’ll make Delivery Hero the go-to platform for a broad range of products, helping us grow faster and deliver more value to customers around the world. In this role, you will lead a squad of 4 to 7 data scientists and ML engineers, taking full technical ownership and accountability for delivery within your squad. You will work at the intersection of tech and product, translating complex business challenges into robust data science solutions and defining the technical strategy to drive growth through innovative promotional strategies. We are reinventing online shopping by building a scalable product ecosystem that optimizes operational processes and enhances user experience. Define and own the technical strategy and roadmap for the Dynamic Promo squad, ensuring alignment with business goals. Translate ambiguous business problems into well-defined technical data science items that your team can work on effi
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